Motion tracking system for real time adaptive imaging and spectroscopy

ABSTRACT

Current MRI technologies require subjects to remain largely motionless for achieving high quality magnetic resonance (MR) scans, typically for 5-10 minutes at a time. However, lying absolutely still inside the tight MR imager (MRI) tunnel is a difficult task, especially for children, very sick patients, or the mentally ill. Even motion ranging less than 1 mm or 1 degree can corrupt a scan. This invention involves a system that adaptively compensates for subject motion in real-time. An object orientation marker, preferably a retro-grate reflector (RGR), is placed on a patients&#39; head or other body organ of interest during MRI. The RGR makes it possible to measure the six degrees of freedom (x, y, and z-translations, and pitch, yaw, and roll), or “pose”, required to track the organ of interest. A camera-based tracking system observes the marker and continuously extracts its pose. The pose from the tracking system is sent to the MR scanner via an interface, allowing for continuous correction of scan planes and position in real-time. The RGR-based motion correction system has significant advantages over other approaches, including faster tracking speed, better stability, automatic calibration, lack of interference with the MR measurement process, improved ease of use, and long-term stability. RGR-based motion tracking can also be used to correct for motion from awake animals, or in conjunction with other in vivo imaging techniques, such as computer tomography, positron emission tomography (PET), etc.

This application claims priority to US provisional patent application60/802,216 filed May 19, 2006, incorporated herein by reference.

TECHNICAL FIELD

This invention relates generally to the field of medical imaging, andmore specifically to a system for correcting defects in medical imagesthat are caused by a patient's movement during long duration in vivo (inthe living body) scans, such as magnetic resonance scans.

BACKGROUND ART

“Tomographic” imaging techniques make images of multiple slices of anobject. Multiple tomographic images can then be aligned and assembledusing a computer to provide a three dimensional view. Some commonly usedtomographic imaging techniques include magnetic resonance imaging (MRI)and magnetic resonance spectroscopy (MRS) techniques, which are idealfor assessing the structure, physiology, chemistry and function of thehuman brain and other organs, in vivo. Because the object of interest isoften imaged in many slices and scanning steps in order to build acomplete three dimensional view, scans are of long duration, usuallylasting several minutes. To increase resolution (detail) of atomographic scan, more slices and more scanning steps must be used,which further increases the duration of a scan. Magnetic resonance andother long duration imaging techniques (including tomographictechniques), now known or hereafter invented (hereinafter collectivelyreferred to as “MR” or “MRI”) can also afford relatively high spatialand temporal resolution, are non-invasive and repeatable, and may beperformed in children and infants.

In addition to MR, other types of scans require multiple repeatedexposures, separated in time, of an entire (not slices) object (such asan organ), such as angiograms, in which a dye is injected into a bloodvessel and then scans separated in time are taken to determine how andwhere the dye spreads. These types of scans that detect motion inside apatient or other object over time (“digital angiography systems”) canalso have a long duration, and be subject to the problem of patient orobject motion.

Many tomographic imaging techniques rely on detecting very smallpercentage changes in a particular type of signal, which makes thesetechniques even more susceptible to movements. In functional magneticresonance imaging, for example, changes in the properties of blood inbrain areas activated while subjects are performing tasks causes smallsignal changes (on the order of a few percent) that can be detected withMR. However, these small signal changes may easily be obscured by signalchanges of similar or even greater size that occur during unintentionalsubject movements.

Because tomographic techniques require that so many images be taken(because so many slices and scanning steps are necessary), the scan hasa long duration, so that motion of the subject is a substantial problemfor acquiring accurate data. Consequently, subjects commonly arerequired to lie still to within one millimeter and one degree overextended time periods. Similar requirements exist for other modemimaging techniques, such as Positron Emission Tomography (PET), SinglePhoton Emission Computerized Tomography (SPECT) and “computertomography” (CT). These strict requirements cannot be met by manysubjects in special populations, such as children and infants, very sickpatients, subjects who are agitated perhaps due to anxiety or drug use,or patients with movement disorders, resulting in data with motionartifacts. Similarly, it is exceedingly difficult to perform scans inawake animals.

The basic problem is that it may take several minutes for a scan to becompleted, but the patient or other object being scanned cannot remainstill for several minutes. Further, the space for a patient or otherobject being scanned (the “scanning volume”) in an MR machine is verylimited—there is very little space in an MR machine once a patient hasbeen positioned inside for a scan.

Several techniques have been developed over the past decades to reducethe sensitivity of scans to motion of the patient or other object beingscanned.

Early techniques utilized specially designed scan sequences(“first-order flow/motion compensation”) to minimize the effects ofmotion. While these approaches are particularly useful for reducingartifacts (or imaging errors) due to flowing blood, swallowing or eyemovements, they afford little improvement during movements of entireorgans, such as head movements.

Articles entitled “Self-navigated spiral fMRI: interleaved versussingle-shot” by Glover GH, et al, in Magnetic Resonance in Medicine 39:361-368 (1998), and “PROPELLER MRI: clinical testing of a noveltechnique for quantification and compensation of head motion” by ForbesK, et al, in the Journal of Magnetic Resonance Imaging 14(3): 215-222(2001), both incorporated herein by reference, disclose how improvedsampling schemes for the MRI data can reduce sensitivity to motion.These techniques can reduce motion sensitivity of MR scans under certainconditions, but cannot eliminate errors from motion under all conditionsor for very quick movements.

With certain modern ultra-fast “single-shot” imaging techniques (such as“echo-planar imaging”), the entire head (or other organ of interest) isscanned continuously every few seconds (over the course of minutes), forinstance, for “functional MRI”. This makes it possible to determine the“pose”, defined as position and rotation, of the head at each instantrelative to the initial pose, using image registration (alignment ofimages). Once the pose for a given instant is known (relative to theinitial image), the scanner's image-for that instant can be re-alignedto the initial image. For example, the article entitled “Processingstrategies for time-course data sets in functional MRI of the humanbrain” by Bandettini P A, et al, in Magnetic Resonance Medicine 30:161-173 (1993), incorporated herein by reference, disclosed howrealignment of MRI volumes (consisting of multiple slices) can be usedto correct for head motion in functional MRI time series. However, thesemethods are inherently slow because they use MRI, i.e. they correctmovements only every few seconds, and are unable to correct for motionin certain directions (orthogonal to the scan planes; in other words,towards or away from the planes in which the scans are being taken).

While all of these techniques reduce sensitivity to subject motion,several problems remain. One major problem is related to the manner inwhich typical tomographic imaging methods acquire data. Specifically,the data for each cross section (slice) is acquired by moving step bystep along “lines” in a mathematical space (“k-space”). The dataacquisition step is typically repeated hundreds of times until all linesin the k-space have been filled. For all methods described above, evenif motion sensitivity for each individual acquisition (defining a linein k-space) is reduced, these methods typically do not account forvariations in head pose amongst the different k-space lines. Second, themethods poorly tolerate fast movements within individual acquisitionsteps. Finally, one of the most significant issues is that none of thesetechniques can be applied universally across all the various scanningmethods (pulse sequences—the order and manner in which slices areimaged) used in MRI or other tomographic scanning techniques.

One of the most promising approaches to motion correction is to trackthe pose of the head, brain or other organ of interest (or other object)in real time, during a scan, and to use this pose information tocompensate for the detected motion in data acquisitions for subsequentslices within the same scan. This is called adaptive imaging, becausethe image is adapted during the scan to compensate for the detectedmotion.

One important aspect of adaptive imaging is the accuracy (or“resolution”) of the motion tracking system. Because of the highresolution needed for medical imaging, the motion tracking system mustalso have a high resolution, because the motion tracking system'sinformation will be used to align the images of each slice. If themotion tracking system's resolution is high enough, each of the scanimages can be accurately aligned (registered) despite a patient'smotion.

An article entitled “Prospective multiaxial motion correction for FMRI”by Ward HA, et al, in Magnetic Resonance in Medicine 43:459-469 (2000),incorporated herein by reference, discloses the use of “navigator”signals to estimate the pose of the head and to dynamically correct forhead motion.

An article entitled “Spherical navigator echoes for full 3D rigid bodymotion measurement in MRI” by Welch E B, et al, in Magnetic Resonance inMedicine 47:32-41 (2002), incorporated herein by reference, disclosesthe use of an MR-based navigator for adaptive motion correction in MRI.

Similarly, an article entitled “Endovascular interventional magneticresonance imaging.” by Bartels L W, et al, in Physics in Medicine andBiology 48(14): R37-R64 (2003), and another article entitled “Real-time,Interactive MRI for cardiovascular interventions” by McVeigh E R, et al,in Academic Radiology 12(9): 1121-1127 (2005), both of which areincorporated herein by reference, disclose the use of smallradiofrequency (RF) coils for tracking catheters during interventionalMRI.

While these MR-based “adaptive MRI” techniques provide good results inmany situations, they intrinsically interfere with MR acquisitions, workonly for a limited number of MR sequences, and are limited to measuringthe position or pose a few times per second only.

In order to overcome these shortcomings, recent approaches to real time(“on the fly”) motion correction utilize optical techniques to tracksubject motion, rather than MR-based methods. The pose information fromthe tracking system is sent to the scanner and used by the scanner tocompensate for the motion in real time. Optical systems are verysuitable among alternative tracking technologies because they provideaccurate, non-contact sensing with a passive and non-magnetic target. Inparticular, stereovision (SV) systems have been used for motion trackingfor medical imaging.

Stereovision systems employ a target with 3 or more visible landmarks,and at least 2 tracking cameras. By detecting the landmarks in imagescaptured by the cameras and comparing their measured positions andshapes to the known shape of the target, the target position andorientation can be determined. SV systems offer important featuresincluding sub-millimeter accuracy when fully calibrated, and updaterates limited only by the camera and computing hardware.

However, SV systems have three limitations for adaptive MR imaging: (1)measurement accuracy decreases as the distance between the camerasbecomes smaller, (2) the accuracy of orientation measurement decreasesas the target becomes smaller; and (3) SV systems have high sensitivityto-errors in internal calibration, i.e. small errors in the relativeposition or rotation of the cameras may cause large errors in themeasured target pose. Therefore, SV systems require periodicrecalibration. However, accurate calibration has to be performedmanually, using a specialized calibration tool or target, is timeconsuming, and cannot be done while patients are being scanned.

Furthermore, stereovision systems achieve their best accuracy when theseparation distance between the cameras is comparable to the distancebetween the cameras and the target. However, this ideal separation isnot possible in an MR scanner because the opening to the scanning volume(the volume which can be scanned by the scanner) is relatively narrow,making it impossible to move the cameras sufficiently far apart andstill view into the scanning volume. Additionally, tracking with SVcameras works optimally with larger tracking targets; however, the spacein the MR or other scanner environment is very limited.

As noted above, slight errors in the internal calibration of SV systemscan produce large measurement errors. For example, an article entitled“Prospective Real-Time Slice-by-Slice 3D Motion Correction for EPI Usingan External Optical Motion Tracking System” by

Zaitsev, M C et al, ISMRM 12, Kyoto (2004), which is incorporated hereinby reference, tested the use of an SV system for adaptive functionalMRI. The system was able to provide 0.4 mm accuracy when ideallycalibrated. However, the study contains information showing that a tiny1/100th degree change in the camera alignments can produce a 2.0 mmerror in the position measurement and the study co-authors privatelycommunicated to the present inventors that maintaining calibration wasimpracticably difficult. Even with extremely careful and rigidengineering of the camera module of an SV system, a measurement drift onthe order of 1 mm can be observed while the SV motion tracker warms up,and recommend warm-up periods are 1 to 1.5 hours to avoid drift.Tremblay M, Tam F, Graham S J. Retrospective Coregistration ofFunctional Magnetic Resonance Imaging Data Using External Monitoring.Magnetic Resonance in Medicine 2005; 53:141-149, incorporated herein byreference.

The prior art has no means to track or correct for these slow changeswhile the medical imaging system is in service, imaging patients. Theerror which accumulates in the co-registration, because of loss ofcamera calibration, is a severe problem for motion compensation inmedical imaging using an external tracking system.

As a result, an SV tracking system requires frequent recalibration toaccurately determine its position relative to the imaging system. Therecalibration procedure involves scanning a specialized calibration toolor sample (“phantom”) at multiple, manually-adjusted positions, bothwith the Medical imaging system and the SV system. An article entitled“Closed-form solution of absolute orientation using unit quatemions” byHorn, B K P, J. Opt. Soc. Am. 1987; 4:629-642, which is incorporatedherein by reference, describes the commonly used “absolute orientation”method. However, since time on a medical imaging system is limited andexpensive, removing patients and conducting repeated recalibration witha specialized calibration tool is prohibitively expensive.

Furthermore, Zaitsev et al utilized a relatively large reflectivemarker, approximately 10 cm (4 inches) in size, which was affixed to thesubjects' head in the scanner by means of a bite bar. While a bite barmay be tolerated by healthy and cooperative volunteers, it is animpractical solution for sick or demented patients, or young children.

Therefore, while stereovision systems are able to track subject motionfor use with adaptive imaging techniques when conditions are ideal, theuse of SV systems for routine clinical scans proves impractical due tocumbersome recalibration procedures, instabilities over time, andawkward size and attachment of tracking markers (i.e. large markerrequiring use of a bite bar).

Motion tracking can be improved using prediction means to predictmotion, including (without limitation) motion filter and predictionmethods. For adaptive MR imaging, the scanner controller requires valuesof the subject pose at the exact instant adjustments to the scan areapplied (Scanning Timing Information). The determination of the subjectpose based on actual measurements is an estimation problem. The simplestestimator takes the most recent measurement as the current pose. Thissimple estimator has been used frequently, for example in an articleentitled “Prospective Real-Time Slice-by-Slice 3D Motion Correction forEPI Using an External Optical Motion Tracking System” by Zaitsev, M. C.,et al, ISMRM 12, Kyoto (2004), incorporated herein by reference.

However, this simple estimator neglects three-types of information thatcan improve the accuracy of the estimate of subject pose: (1)measurements prior to the most recent measurement may add information(reduce the covariance of the estimate) if those prior measurementsdisclose a velocity of the subject's motion; (2) a biomechanical model,in conjunction with the measurement statistics, can be used to constrainthe estimated motion (the subject's body only moves in certain ways);and (3) information about the lag time between the pose measurement andthe time of the MR scans. By utilizing these additional sources ofinformation, the accuracy of motion tracking and thus of adaptiveimaging will be enhanced.

Extended Kalman filtering, which is essentially model-based filteringwith simultaneous estimation of the signals and their statistics, isstatistically optimal in certain cases and is the most effectiveframework for incorporating information of types (1), (2) and (3).Kalman filtering has a long history of use in aerospace applications,such as target tracking, aircraft guidance and formation flying ofspacecraft, for example in U.S. Pat. No. 5,886,257 “Autonomous LocalVertical Determination Apparatus and Methods for a Ballistic Body,”incorporated herein by reference, which teaches the use of Kalmanfiltering applied to inertial signals. Kalman filtering has also beenpreviously demonstrated for head motion tracking, for example in“Predictive Head Movement Tracking Using a Kalman Filter”, IEEE Trans.on Systems, Man, and Cybernetics Part B: Cybernetics 1997; 27:326-331,by Kiruluta A, Eizenman M, and Pasupathy S, incorporated herein byreference. Kalman filtering is also disclosed in U.S. Pat. No. 6,484,131entitled “Localization and Tracking System”, incorporated herein byreference.

Of course, persons of ordinary skill in the art are aware that theprediction means can be implemented in hardware, software, or by othermeans, and that there are equivalent processes and algorithms to performthe prediction function of the motion filtering and prediction meansdisclosed above.

U.S. Pat. Nos. 5,936,722, 5,936,723 and 6,384,908 by Brian S. R.Armstrong and Karl B. Schmidt, et al, which are incorporated herein byreference, disclose “Retro-Grate Reflectors”, or RGRs, which allowaccurate and fast position measurements with a single camera and asingle, relatively small and light orientation marker. The RGR allowsthe visual determination of orientation with respect to the six degreesof freedom (the three linear directions of left and right, up and down,and forward and back, plus the three rotational directions of roll(rotation around a horizontal axis that points straight ahead), pitch(rotation around a horizontal axis that points side to side) and yaw(rotation around a vertical axis that points up and down)) by viewing asingle marker. Pose (position and rotation) is orientation with respectto the six degrees of freedom. As used herein, an object orientationmarker is any marker, such as an RGR marker, from which at least threedegrees of freedom can be determined by viewing or otherwise remotelydetecting the marker.

DISCLOSURE OF INVENTION

Conceptually, the present invention generally includes a motion trackingsystem for an object in the scanning volume of a scanner, comprising:

an object orientation marker attached to the object;

a detector that repeatedly detects poses of the object orientationmarker;

a motion tracking computer that analyzes the poses of the objectorientation marker to determine motion of the object between therepeated detections and to send tracking information to the scanner todynamically adjust scans to compensate for motion of the object.

More specifically, the invention comprises:

an object orientation marker attached to the object;

a camera that records repeated images;

a mirror in a fixed position with respect to the scanner positioned sothat the camera records repeated reflected images of the orientationmarker in the mirror;

a motion tracking computer that analyzes the repeated reflected imagesof the object orientation marker to determine motion of the objectbetween the repeated images and to send tracking information to thescanner to dynamically adjust scans to compensate for motion of saidobject.

Another aspect of the invention is a process for compensating forpatient motion in the scanning volume of a scanner that has a motiontracking system, without a specialized calibration tool, even if themotion tracking system is out of alignment with the scanner, comprising:

recording the patient motion both in scans of the patient by the scannerand in the motion tracking system, whereby the patient motion issimultaneously recorded in the coordinate frame of the scanner and inthe coordinate frame of the motion tracking system;

updating the measurement coordinate transformation from the motiontracking system coordinate frame to the scanner coordinate frame tocompensate for drift and other calibration inaccuracies;

transforming patient motion recorded in the coordinate frame of themotion tracking system into patient motion in the coordinate frame ofthe scanner using the updated measurement coordinate transformation.

A general embodiment of this invention comprises an object orientationmarker attached to an object;

a camera that views the object orientation marker directly;

a first mirror in a fixed position with respect to the scannerpositioned so that the camera can view a reflected image of the objectorientation marker in the first mirror, so that the camerasimultaneously records repeated direct images and repeated reflectedimages of the object orientation marker; and

a motion tracking computer that analyzes both the repeated direct imagesand the repeated reflected images of the object orientation marker todetermine motion of the object between the repeated images and to sendtracking information to the scanner to dynamically adjust scans tocompensate for motion of said object;

whereby the mirrors and camera can be internally calibrated by analyzingthe repeated direct images and the repeated reflected images of theobject orientation marker.

A preferred embodiment of the present invention comprises:

a camera that records repeated images;

an object orientation marker attached to the object;

a first mirror in a fixed position with respect to the scannerpositioned so that the camera can view the object orientation marker inthe first mirror;

a second mirror in a fixed position with respect to the first mirrorpositioned so that the camera can view reflected images of the objectorientation marker in the second mirror simultaneously with reflectedimages of the object orientation marker in the first mirror;

a motion tracking computer that analyzes repeated reflected images ofthe object orientation marker in the first mirror and repeated reflectedimages of the object orientation marker in the second mirror todetermine motion of the object between the repeated images and to sendtracking information to the scanner to dynamically adjust scans tocompensate for motion of said object.

Another preferred embodiment of the present invention comprises:

a camera that records repeated images;

an object orientation marker attached to the object;

a first mirror in a fixed position with respect to the scannerpositioned so that the camera can view the object orientation marker inthe first mirror;

a mirror orientation marker in a fixed position with respect to thefirst mirror positioned so that the camera can view a direct image ofthe mirror orientation marker simultaneously with a reflected image inthe first mirror of the object orientation marker;

a motion tracking computer that analyzes repeated reflected images ofthe object orientation marker in the first mirror and repeated directrepeated images of the mirror orientation marker to determine motion ofthe object between the repeated images and to send tracking informationto the scanner to dynamically adjust scans to compensate for motion ofsaid object.

Still another preferred embodiment of the invention comprises:

a camera that records repeated images;

an object orientation marker attached to the object;

a first mirror in a fixed position with respect to the scannerpositioned so that the camera can view the object orientation marker inthe first mirror;

a second mirror in a fixed position with respect to the first mirrorpositioned so that the camera can view reflected images of the objectorientation marker in the second mirror simultaneously with reflectedimages of the object orientation marker in the first mirror;

a mirror orientation marker in a fixed position with respect to thefirst mirror positioned so that the camera can view direct images of themirror orientation marker simultaneously with reflected images of theobject orientation marker in both the first mirror and the secondmirror;

a motion tracking computer that analyzes repeated reflected images ofthe object orientation marker in the first mirror, repeated reflectedimages of the object orientation marker in the second mirror andrepeated direct images of the mirror orientation marker, to determinemotion of the object between the repeated images and to send trackinginformation to the scanner to dynamically adjust scans to compensate formotion of said object.

An additional feature of the present invention is that the mirrors andcamera can be internally calibrated by analyzing the repeated directimages and the repeated reflected images.

Optionally, patient motion can be recorded both by scans of the objectby the scanner and by repeated images of the object orientation marker,so that such patient motion is recorded in coordinate frames of both thescanner and of the detector and mirrors, whereby patient motion recordedin the coordinate frame of the detector and mirrors can be transformedinto patient motion in the coordinate frame of the scanner.

An additional optional feature of the invention includes predictionmeans to predict orientation of the object at times when scans will betaken by the scanner, including motion filtering and prediction.

Of course, the scanner can be selected from the group consisting of MRscanners, PET scanners, SPECT scanners, CT scanners-and digitalangiography systems.

Operably the object orientation marker indicates pose in at least 3degrees of freedom, but preferably the object orientation markerindicates pose in 5 degrees of freedom, and optimally in 6 degrees offreedom.

Preferably, the object orientation marker is an RGR.

In general terms, the invention comprises:

an adaptive imaging system;

a motion tracking system; and

a motion filtering and prediction system;

wherein the motion tracking system provides tracking information to theadaptive imaging system to dynamically adjust scans to compensate formotion of said object; and

wherein the motion filtering and prediction system provides predictedpose of the object when the imaging system takes scans.

Briefly, and in general terms, the present invention provides for asystem for automatic real-time correction of subject motion during longduration scans, including (but not limited to) “tomographic” (orcross-sectional) imaging, specifically MRI scans. The present inventionis a motion tracking system that is MRI-compatible, highly accurate,robust, self-calibrating, has a potential time resolution in themillisecond range, and can be integrated with any existing MR technique.The adaptive MR system has 3 main components, as shown in FIG. 1: (1)RGR-based tracking system, (2) interface between tracking system and MRscanner, and (3) MR scanner providing scanning sequences that allowdynamic adjustment of geometric scanning parameters (such as slicelocations and orientations). The camera-based system relies onRetro-Grate Reflectors, or RGRs, which allow accurate and fast posemeasurements with a single camera and a single, relatively small marker(approximately 1 cm size). Pose updates from the tracking system aresent to the MRI scanner via the interface. Tomographic scanning methodsmake it possible to image multiple cross-sections (“slices”) of thebody; each slice is defined by a position and rotation in space. The MRscanning sequences continuously read the pose information from thetracking system, and the slice locations and rotations are updateddynamically, such that scanning planes or volumes track the poses of theobject (such as an organ) to which the target is attached. This resultsin scans that are virtually void of motion-artifacts. Very fastmovements with velocities of 100 mm/sec or greater can be corrected,which represents an approximate 10 to 100-fold improvement over currenttechniques.

One important component of the presently preferred embodiment of thisinvention is the Retro-Grate Reflector (RGR), a new tool that makes itpossible to accurately determine the 3 locations and 3 rotations (“6degrees of freedom” or “pose”) of a target from a single image. An RGRtarget is illustrated in FIG. 13. It is constructed by applying artworkon the front and back of a transparent substrate, such as a glass orplastic plate. The artwork includes a StarBurst landmark, shown in thecenter of FIG. 13, and circular landmarks. Also included are front andback gratings to produce a series of banded patterns (“moire” patterns),which are shown as light and dark fringes in FIG. 13.

The moire patterns of the RGR target are designed to be exquisitelysensitive to changes in orientation. As a result, the RGR system is ableto accurately determine all 6 degrees of freedom (3 translations and 3rotations) from a single camera image. Of course, an RGR can be used toextract less than 6 degrees of freedom.

In the context of adaptive imaging to correct for subject motion, RGRmotion tracking addresses the shortcomings of stereovision by: (1)incorporating only one camera, thus removing the requirement for asignificant separation between cameras, and (2) interpreting moirepatterns so that high accuracy can be achieved even if the objectorientation marker (also referred to as a target or tag) is small, and(3) providing redundant information for use in detecting and correctingdrift and other calibration inaccuracies by internal calibration.

If desired, further innovations (described below) allow for 3)simultaneous motion tracking and determination of the internalcalibration, 4) use of two or more “visual paths” to avoid loss of sightduring large movements, 5) a 10-fold increase in tracking accuracycompared to stereovision, and 6) continuous automatic calibration (or“auto-tuning”) of the system in order to eliminate the effect of driftand other calibration inaccuracies, such as those due to temperaturechanges, vibration, etc.

One innovation is to use a mirror to detect an object orientationmarker. A mirror shall include any device to allow an object orientationmarker to be viewed along an indirect line of sight, including, withoutlimitation, a prism, a beam splitter, a half silvered mirror, fiberoptics, and a small camera.

Another innovation is to incorporate motion filtering and prediction toimprove performance of a limited-quality motion sensing means. Motionfiltering refers to using information about an object's prior positionsto infer its motion and thereby improve accuracy in determining pose(over methods which look only at the most recent position and ignoreprior positions).

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a conceptual side elevational view of a system for RGR-basedmotion tracking for real-time adaptive MR imaging and spectroscopy.

FIG. 2 is a flow chart of steps for adaptive MR imaging in analternative embodiment, incorporating RGR-based motion sensing foradaptive MR imaging.

FIG. 3 is a flow chart of steps for RGR-based adaptive MR imaging in thepreferred embodiment, incorporating RGR-based adaptive MR imaging andoptional motion filtering and prediction.

FIG. 4 is a flow chart of steps for adaptive MR imaging in analternative embodiment, incorporating motion sensing by any suitablemeans such as MR scan analysis and optional motion filtering andprediction.

FIG. 5 is a flow chart of steps for adaptive MR imaging in analternative embodiment in which the motion filtering is performedseparately.

FIG. 6 is a side elevational view of the physical layout of a preferredembodiment of adaptive RGR-MRI configuration.

FIG. 7 is a top plan view of the embodiment of FIG. 6.

FIG. 8 is a back elevational view of the embodiment of FIG. 6.

FIG. 9 is a camera view, showing the mirrors and object orientationmarkers in the camera in the embodiment of FIG. 6, and also showingplacement of optional RGRs on mirrors.

FIG. 10 is a conceptual diagram illustrating that motion of the subjectcan be determined in both the coordinate frames of the motion trackingsystem and of the MR machine.

FIG. 11 is a conceptual flow chart illustrating a system for continuoustuning (“Auto-tuning”) of the co-registration transformation between aMotion Tracking system and a Medical Imaging system.

FIG. 12 is a flow chart of steps for Auto-tuning for automatic andcontinuous adjustment of the Co-registration Transformation between aMotion Tracking system and a Medical Imaging system.

FIG. 13 is a drawing of an RGR target.

BEST MODES FOR CARRYING OUT INVENTION

FIGS. 1 and 2 illustrate the essential elements of the presentlypreferred embodiments of a system for motion tracking for real-timeadaptive imaging and spectroscopy. The best modes are illustrated by wayof example using a patient in an MR scanner and RGR object orientationmarker, but of course, other objects can be scanned besides patients,other scanners can be used besides MR scanners, and other objectorientation markers can be used besides RGRs.

As shown in FIG. 1, a patient P is imaged in a scanning volume V insidean MR scanner magnet 20. An RGR tag or target 30 is affixed to thepatient P near the organ of interest being scanned (e.g., the head). Adetector, such as a camera 40 (the “RGR Camera”) outside the scannermagnet 20 observes the RGR target 30, either directly or optionally viaone or more mirrors on the wall of the scanner bore or in some otherconvenient location (not shown). As also shown in FIG. 2, the RGR Camera40 is connected to the RGR Processing Computer 50. The RGR ProcessingComputer 50 performs several functions, including analyzing images 60 ofthe RGR to produce RGR Motion Information. Additionally, an accurateclock in the RGR Processing Computer 50 produces Timing Informationrelated to the RGR Motion Information to provide Motion and TimingInformation 70.

A Scanner Control and Processing Computer 100 is connected to the MRScanner 120 and also to the RGR Processing Computer 50. RGR Motion andTiming Information 70 is passed from the RGR Processing Computer 50 tothe Scanner Control and Processing Computer 100. In one embodiment,Timing Information related to the MR scan (Scanner Timing Information)is produced by the Scanner Control and Processing Computer 100 andpassed to the RGR Processing Computer 50 with a request for RGR MotionInformation. The RGR Processing Computer 50 uses the Scanner TimingInformation in conjunction with the RGR Motion Information and RGRTiming Information to produce Motion Information at time instantsdetermined by the Scanner Control and Processing Computer 100. Both thescanner and the motion tracking system have inherent lag times betweenacquiring an image and completing the image, due to computation delaysand other factors. The motion tracking system's lag time in acquiringimages may be on the order of milliseconds, but the scanner's lag timein acquiring images may be on the order of seconds to minutes.

The Scanner Control and Processing Computer 100 utilizes RGR MotionInformation from the RGR Processing Computer 50 and makes calculationsto adapt the MR Pulse Sequence (the sequence of pulses used to acquiretomographic images) to the motion information. The adapted MR PulseSequence parameters are used to drive the MR Scanner 120.

FIG. 3 provides a flow chart of the steps of the preferred embodiment ofRGR-based adaptive MR imaging and spectroscopy using optional motionfiltering and prediction. System elements of RGR Camera, RGR Lightingand RGR target are used to obtain RGR Motion Tracking Images. The RGRImages are passed to the RGR Processing Computer where they areanalyzed, which produces RGR Motion and RGR Timing Information. Thisinformation is optionally passed to a Motion Filtering and Predictionroutine, which also receives Scanner Timing Information in the form oftime values for future instants at which the Scanner Control andProcessing Computer will apply Motion Information. The Motion Filteringand Prediction element analyzes a plurality of recent RGR Motion andTiming Information as well as Scanner Timing information to produceAdjusted Motion Information, which is the best estimate of the subject'spose at the future time indicated in the Scanner Timing Information. TheAdjusted Motion Information corresponding to the Scanner TimingInformation is passed to the Scan Control and MR Pulse SequenceGeneration element.

The Scan Control and MR Pulse Sequence Generation element receivesAdjusted Motion Information for corresponding Scanner Timing Informationand generates Adapted Pulse Sequence Parameters, which are executed onthe MR Scanner, thus realizing RGR-based adaptive MR imaging andspectroscopy.

Essentially, the motion tracking information is used to predict thechange in pose of the patient due to movement, and the predicted pose issent to the scanner, which then dynamically adjusts the pose of eachscan plane or volume to compensate for the patient's movement.

Comparing the flow chart of FIG. 2 with the flow chart of FIG. 3, in thepreferred embodiment, the “Motion Filtering and Prediction” routines runon the RGR Processing Computer 50, and there is no separate computer forthe optional motion filtering and prediction calculations, which arerelatively minor from the standpoint of computer burden. In alternativeembodiments, the Motion Filtering and Prediction routines could run on aseparate computer (or hardware or software), or on the Scanner Controland Processing Computer.

FIG. 4 illustrates an alternative embodiment of the invention. In thisembodiment, any suitable motion and timing sensing means is used,including, but not limited to, motion sensing by image analysis, as isknown in the prior art, such as commercially available Stereo Visionsystems. The innovation in this embodiment is to employ a MotionFiltering and Prediction element to analyze a plurality of recent RGRMotion and Timing Information as well as Scanner Timing information toproduce Adjusted Motion Information, which is the best estimate of thesubject pose at the time indicated in the Scanner Timing Information.The Adjusted Motion Information is passed to the Scan Control and MRPulse Sequence Generation element.

The Scan Control and MR Pulse Sequence Generation element receivesAdjusted Motion Information and generates Adapted Pulse SequenceParameters, which are sent to the MR Scanner and executed, thusrealizing RGR-based adaptive MR imaging and spectroscopy.

Yet another embodiment is illustrated in FIG. 5. In this alternativeembodiment the Motion Filtering calculations are executed by a MotionTracking system computer, and the Motion Filter State and TimingInformation are transferred to the Scanner Control and ProcessingComputer. The Prediction portion of the Motion Filtering and Predictionalgorithm utilizes the Motion Filter State and Timing Information, aswell as Scanner Timing Information that is internal to the ScannerControl and Processing Computer, to predict the subject pose at the timeindicated in the Scanner Timing Information.

FIGS. 6 to 8 show various views of the presently preferred embodiment ofthe RGR-based adaptive MR imaging and spectroscopy system. Each viewillustrates the relationship of the scanning volume V (here, the bore ofan MR Scanner magnet), detector (here, a camera 40) and objectorientation marker 30 (preferably an RGR tag, target or marker). Thecamera 40 is preferably outside and behind the scanner magnet 20. Alsoseen in the figures are optional mirrors M1 and M2, each with or withouta separate optional RGR, which are used to allow the camera 40 to beplaced outside a direct line of sight with the object orientation marker30, to avoid blockage and for other reasons. Considering the openingsthat are typically available in the coil surrounding the subject's headduring MR scans, the top position point-of-view offers superiormeasurement accuracy. FIG. 6 also shows the position of the origin O ofthe medical imaging coordinate frame.

In one preferred embodiment of the invention, if the patient requires abrain or head scan, one RGR target 30 (the “mobile,RGR tag”) is affixedto the side of the nose of the patient. This particular location has theadvantage of being relatively immobile during head movements. However, aperson knowledgeable in the art will recognize that the mobile RGR tagmay also be affixed to other parts of the body.

In one preferred embodiment of the invention, a single mirror is used toobserve the mobile RGR target from the camera.

In another preferred embodiment of the invention, a mirror orientationmarker (a “stationary marker”), preferably an RGR tag, is mounted on thesingle mirror. This mirror RGR tag is directly visible from the camera,and is being analyzed continuously in addition to the mobile RGR on theorgan of interest. Analyzing the pose of the mirror RGR makes itpossible to ensure the “internal calibration” of the RGR trackingsystem, i.e. to ensure the relative position of the camera and mirrorare known accurately.

In yet another embodiment of the invention, two or more mirrors are usedto observe the mobile RGR from the camera. The mirrors are arranged suchthat the reflected image of the mobile RGR is visible to the camera inall of them. Having two or more mirrors makes it possible to observe themobile RGR on the patient, and determine the patient pose, even if oneof the views is obstructed.

In another preferred embodiment of the invention, a single cameraobserves the mobile RGR on the subject directly as well as indirectly,creating two lines of sight. The camera is pointed towards asemi-transparent mirror (or prism) that splits the optical path intotwo. The direct, non-reflective optical path is pointed towards themobile RGR, allowing a direct line of sight. The reflective optical pathleads towards a second mirror or prism (fully reflective), and isredirected towards the RGR. One or both of the two mirrors or prisms canbe equipped with RGRs, to enable internal calibration. Thisconfiguration allows mounting of the camera inside the MRI scanner bore,and provides the same advantages as the two-mirror/stationary RGR systemdisclosed herein.

In yet another embodiment of the invention, a single-camera is pointingdirectly towards the mobile RGR. However, half the field-of-view of thecamera is obstructed by a mirror or prism. The reflected optical pathleads towards a second mirror or prism, that redirects the optical pathtowards the RGR. One or both of the two mirrors or prisms can beequipped with RGRs, to enable internal calibration. This configurationallows mounting of the camera inside the MRI scanner bore, and providesthe same advantages as the two-mirror/stationary RGR system disclosedherein.

In another preferred embodiment of the invention, additional mirrororientation markers, preferably stationary RGR tags, are mounted on eachof two or more mirrors, or on brackets holding one or more of themirrors. The mirrors and stationary RGR tags are arranged such that themobile RGR tag and all the stationary RGR tags are visible from thecamera. All stationary RGR tags, as well as the mobile RGR tag on thepatients, are being analyzed continuously. It would be expected that theaccuracy of optical measurements would suffer if more optical elementsare introduced into the measurement system because of the need tomaintain more elements in alignment. However, by analyzing all theinformation from all RGRs simultaneously, this particular embodiment ofthe invention results in a dramatic and unexpected improvement inaccuracy of the tracking system, such that the tracking accuracy isunexpectedly approximately 10-fold greater than that of a conventionalstereo-vision system

In another embodiment of this RGR-based adaptive MR imaging andspectroscopy system, the tracking camera is installed inside the MRmagnet and observes the mobile RGR target either directly or via one ormore mirrors (each with or without its own stationary RGR). In thisinstance, the camera needs to be shielded to avoid interference with theMR measurement system.

FIG. 9 exemplifies an RGR camera view which would be typical in thepreferred embodiment with two mirrors M1 and M2. Optionally, mirrororientation markers 200A and 200B can be attached to the mirrors M1 andM2. The RGR Camera is arranged to produce an image of the mirrors, andthe mirrors are arranged so that the mobile RGR tag is reflected in bothof the mirrors and two reflected images of the mobile RGR tag 30R1 and302 are visible to the camera. Two (or more) mirrors are used to obtainmultiple views of the RGR target in a single image. Optionally, themirror orientation markers 200A and 200B also can be viewed directly bythe camera.

While the use of two or more mirrors, each with its optional associatedstationary mirror RGR, may seem more cumbersome and error-prone than asingle-mirror configuration, it provides several important andunexpected advantages. First, the multiple views of the mobile RGRtarget provide multiple lines of sight. One advantage of obtainingmultiple views of the RGR target is that at least one view will remainclear and available for motion tracking, even if another view isobscured. A view can be obscured by, for example, a portion of the headcoil that surrounds the head of the subject during functional MRscanning. A second advantage of obtaining multiple views of the mobileRGR target is an unexpected and dramatic improvement in the accuracy ofthe motion tracking system, such that the 2-mirror system isapproximately 10 times more accurate than a stereovision trackingsystem. Therefore, a multi-mirror multi-RGR system provides substantialadvantages that cannot be reproduced with other typical motion trackingsystems, such as a stereovision system.

Yet another preferred embodiment of the invention involves a combinationof any of the embodiments of the RGR-based tracking system describedabove, with a system that makes it possible to automatically andcontinuously calibrate the RGR-tracking system (“auto-tuning”), in orderto eliminate the effect of drift and other calibration inaccuracies inthe camera system. As noted above, because the required co-registrationaccuracy (between the Medical imaging system and the tracking system) isvery high (on the order of 0.1 mm and 0.1 degree for Medical Imaging)and because the elements of prior art measurement systems can be widelyseparated (for example, by several meters for Magnetic Resonanceimaging), thermal drift, vibration and other phenomena can cause thealignment (“co-registration”) between the motion tracking systemcoordinate frame c and scanning system coordinate frame M to change overtime. The prior art has no means to track or correct for these slowchanges while the medical imaging system is in service, imagingpatients. The error which accumulates in the co-registration is a severeproblem for motion compensation in medical imaging using an externalmotion tracking system. Time on a medical imaging system is limited andexpensive, and removing patients and conducting periodic recalibrationwith a specialized calibration tool or target is prohibitivelyexpensive.

FIG. 10 illustrates the coordinate frames of a system for real-timeadaptive Medical Imaging. The system comprises a Motion Tracking System(preferably tracking motion in real time), such as the RGR trackingsystem, which produces timely measurements of the subject pose within amotion tracking coordinate frame ‘c’. Simultaneously, the subject isimaged by a Medical Imaging system, such as an MR Scanner, whichoperates within a medical imaging coordinate frame ‘M’. Improved medicalimages are obtained if (real-time) Motion Information is available tothe Medical Imaging system, but the Motion Information must beaccurately translated (or transformed) from the real-time motiontracking system (coordinate frame ‘c,’) to the coordinate frame ‘M’ ofthe Medical Imaging system. The motion tracking system is considered“calibrated” with respect to the MR system if the mathematicaltransformation leading from one coordinate system to the othercoordinate system is known. However, the calibration (or alignment) ofthe two coordinate systems can be lost, introducing inaccuracies, due todrift over time because of various factors, including heat andvibration.

Motion Information is transformed from frame ‘c’ to frame ‘M’ by a“coordinate transformation matrix”, or “Co-registration transformationT_(C←M)”. The “coordinate transformation matrix” converts or transformsmotion information from one coordinate frame to another, such as fromthe motion tracking coordinate frame c to the medical imaging coordinateframe M. Loss of calibration due to drift, as well as other calibrationinaccuracies, will result in a change over time of the coordinatetransformation matrix, which in turn will lead to errors in the trackinginformation.

U.S. Pat. No. 6,044,308, incorporated herein by reference, describes theAX=XB method of coordinate transformations. This patent teaches the useof the AX=XB method for determining the transformation from a toolcoordinate frame to a robot coordinate frame, where the tool moves withthe end effector of the robot

The co-registration transformation T_(C←M) slowly varies over time (i.e.over the course of many hours or days) due to temperature changes,vibrations and other effects. This variation introduces error into theTransformed Real-time Motion Information for real-time adaptive MedicalImaging.

FIG. 11 illustrates the elements of an embodiment of the system forAuto-tuning for automatic and continuous determination of theco-registration transformation between a Motion Tracking system and aMedical Imaging system. A patient P is imaged inside a Medical Imagingsystem comprising a medical imaging device 220 and a Medical Imaging andControl & Processing Element 240. Simultaneously, a Motion Trackingsystem comprising a motion tracking detector 250, and a motion trackingprocessing element, such as any embodiment of the RGR-tracking system,makes real-time motion measurements. Using the co-registrationtransformation T_(C←M), the real-time Motion Information is transformedfrom the Motion Tracking system coordinate frame to the Medical Imagingsystem coordinate frame.

Concurrent with the processes described above, Delayed Medical ImageMotion Information 260 and Delayed Motion Tracking Motion Information270 is supplied to the Co-registration Auto-tuning Element 280. Thisinformation is delayed because the Medical Image Motion Information isonly available in delayed form and typically much less frequently thanthe information from the tracking system. For instance, ultra-fast MRIscanning sequences, such as echo planar imaging (EPI), make it possibleto scan the entire head, or other organs of interest, every few seconds.From each of these volumetric data sets, it is possible to determinehead position and rotation, with a time resolution of a few seconds.Alternatively, navigator scans can provide position information a fewtimes each second. Displacements of the subject are recorded from bothsources of Motion Information, i.e. from the RGR motion tracking system,as well as an MRI scanner, e.g. registration of EPI-volumes or navigatorscans. By comparing these measured displacements, the Co-registrationAuto-tuning Element adjusts the coordinate transformation matrix T_(C←M)to compensate for changes in the co-registration of the Motion Trackingsystem and the Medical Imaging system. The updated value 290 of thecoordinate transformation matrix T_(C←M) is repeatedly generated andsupplied to the Motion Tracking system for use in transforming theReal-time Motion Information to Medical Imaging system coordinates 300.

In the preferred embodiment of the auto-tuning system, each of the threeprocessing elements is implemented as computer software running on aseparate computer. Those skilled in the art of real-time computersystems will see that other configurations are possible, such as allprocessing elements running on a single computer, or two or morecomputers working in coordination to realize one of the processingelements.

With automatic and continuous tuning of the co-registrationtransformation, the real-time Motion Information produced by the MotionTracking System is accurately transformed into Medical Imaging systemcoordinates, so as to be usable by the Medical Imaging system forreal-time adaptive Medical Imaging, even in the presence of inevitabledrift and other calibration inaccuracies arising from variations overtime of the relative position and orientation of the Motion Tracking andMedical Imaging coordinate frames.

FIG. 12 provides a flow chart of the steps for Auto-tuning for automaticand continuous co-registration of a Motion Tracking system (for instanceany embodiment of the RGR-tracking system described above), with aMedical Imaging system. The Medical Imaging system obtains MedicalImages. These are analyzed by post processing using prior art methods toproduce Delayed Medical Image Motion Information in the form of themeasured displacement of the imaging subject (e.g., the patient's head)between two times, tk1 and tk2. This displacement is measured in theMedical Imaging system coordinate frame.

Concurrently, the Motion Tracking system is used to obtain real-timeMotion Information, which may be transformed into the Medical Imagingsystem coordinates to provide for real-time adaptive Medical Imaging.The Motion Tracking Motion Information is also stored in a buffer. Pastvalues of the Motion Tracking Motion Information from the buffer areused to determine a second displacement of the imaging subject asdetected by the Motion Tracking system, between the two previouslymentioned times, tk1 and tk2. This second displacement is measured inthe Motion Tracking system coordinate frame.

The displacement determined by post processing of the Medical Images andthe displacement determined from the buffered Motion Tracking MotionInformation are passed to the registration routine based on an approachlabeled as “AX=XB methodology”, which is known to the prior art. See,for example, Park, F. C. and B. J. Martin, “Robot Sensor Calibration:Solving AX=XB on the Euclidean Group”, IEEE Transactions on Robotics andAutomation, 1994. 10(5): p. 717-721; Angeles, J., G. Soucy, and F. P.Ferrie, “The online solution of the hand-eye problem”, IEEE Transactionson Robotics and Automation, 2000. 16(6): p. 720-731; Chou J C K, KamelM., “Finding the Position and Orientation of a Sensor on a RobotManipulator Using Quaternions”, The International Journal of RoboticsResearch 1991; 10:240-254; Shiu Y C, Ahmad S., “Calibration ofWrist-Mounted Robotic Sensors by Solving Homogeneous Transform Equationsof the Form AX=XB”, IEEE Transactions on Robotics and Automation 1989;5:16-29; Tsai R Y, Lenz R K, “A New Technique for fully autonomous andefficient 3D robotics hand/eye calibration”, IEEE Journal of Roboticsand Automation 1989; 3:345-358; Wang C C, “Extrinsic Calibration of aVision Sensor Mounted on a Robot”, IEEE Transactions on Robotics andAutomation 1992; 8:161-175, all of which are incorporated herein byreference.

Using this method, the co-registration T_(C←M) is updated.

Therefore, by continuously updating the co-registration information,gradual and inevitable drifts and other calibration inaccuracies in thealignment of the Motion Tracking system and the Medical Imaging systemcoordinate frames are corrected and accurate adaptive compensation forsubject motion is achieved even in the presence of drift and othercalibration inaccuracies in the equipment.

Persons knowledgeable in the art will recognize that the auto-tuningtechnique described in this disclosure may also utilize motioninformation from multiple (more than 2) time points, for instance in theform of filtering, which will generally increase the accuracy of theauto-tuning procedure.

Persons knowledgeable in the art will recognize that the techniquesdescribed in this disclosure may also be applied to medical imagingtechniques other than MRI, such as PET, SPECT, CT, or angiographicscanning.

The optimal embodiment of the RGR-based adaptive motion compensationsystem involves (1) the RGR system shown in FIGS. 6-9, (2) two or moreobservation mirrors, each optionally with its own stationary RGR, and(3) the auto-tuning system.

While the present invention has been disclosed in connection with thepresently preferred best modes described herein, it should be understoodthat there are other embodiments which a person of ordinary skill in theart to which this invention relates would readily understand are withinthe scope of this invention. For example, the present invention shallnot be limited by software, specified scanning methods, target tissues,or objects. For a further example, instead of using a camera or otheroptical imaging device to determine an object's pose, alternativedetectors of pose can be used, including non-imaging detectors andnon-optical detectors, such as magnetic detectors or polarized lightdetectors. Accordingly, no limitations are to be implied or inferred inthis invention except as specifically and explicitly set forth in theattached claims.

Industrial Applicability

This invention can be used whenever it is desired to compensate formotion of a subject, especially while taking a long duration scan.

1. A motion tracking system for an object in the scanning volume of ascanner, comprising: an object orientation marker attached to theobject; a detector that repeatedly detects poses of the objectorientation marker; a motion tracking computer that analyzes the posesof the object orientation marker to determine motion of the objectbetween the repeated detections and to send tracking information to thescanner to dynamically adjust scans to compensate for motion of theobject.
 2. A motion tracking system for an object in the scanning volumeof a scanner, comprising: an object orientation marker attached to theobject; a camera that records repeated images; a mirror in a fixedposition with respect to the scanner positioned so that the camerarecords repeated reflected images of the orientation marker in themirror; a motion tracking computer that analyzes the repeated reflectedimages of the object orientation marker to determine motion of theobject between the repeated images and to send tracking information tothe scanner to dynamically adjust scans to compensate for motion of saidobject.
 3. A process for compensating for patient motion in the scanningvolume of a scanner that has a motion tracking system, without aspecialized calibration tool, even if the motion tracking system is outof alignment with the scanner, comprising: recording the patient motionboth in scans of the patient by the scanner and in the motion trackingsystem, whereby the patient motion is simultaneously recorded in thecoordinate frame of the scanner and in the coordinate frame of themotion tracking system; updating the measurement coordinatetransformation from the motion tracking system coordinate frame to thescanner coordinate frame to compensate for drift and other calibrationinaccuracies; transforming patient motion recorded in the coordinateframe of the motion tracking system into patient motion in thecoordinate frame of the scanner using the updated measurement coordinatetransformation.
 4. A motion tracking system for an object in thescanning volume of a scanner, comprising: an object orientation markerattached to the object; a camera that views the object orientationmarker directly; a first mirror in a fixed position with respect to thescanner positioned so that the camera can view a reflected image of theobject orientation marker in the first mirror, so that the camerasimultaneously records repeated direct images and repeated reflectedimages of the object orientation marker; and a motion tracking computerthat analyzes both the repeated direct images and the repeated reflectedimages of the object orientation marker to determine motion of theobject between the repeated images and to send tracking information tothe scanner to dynamically adjust scans to compensate for motion of saidobject; whereby the mirrors and camera can be internally calibrated byanalyzing the repeated direct images and the repeated reflected imagesof the object orientation marker.
 5. A motion tracking system for anobject in the scanning volume of a scanner, comprising: a camera thatrecords repeated images; an object orientation marker attached to theobject; a first mirror in a fixed position with respect to the scannerpositioned so that the camera can view the object orientation marker inthe first mirror; a second mirror in a fixed position with respect tothe first mirror positioned so that the camera can view reflected imagesof the object orientation marker in the second mirror simultaneouslywith reflected images of the object orientation marker in the firstmirror; a motion tracking computer that analyzes repeated reflectedimages of the object orientation marker in the first mirror and repeatedreflected images of the object orientation marker in the second mirrorto determine motion of the object between the repeated images and tosend tracking information to the scanner to dynamically adjust scans tocompensate for motion of said object.
 6. A motion tracking system for anobject in the scanning volume of a scanner, comprising: a camera thatrecords repeated images; an object orientation marker attached to theobject; a first mirror in a fixed position with respect to the scannerpositioned so that the camera can view the object orientation marker inthe first mirror; a second mirror in a fixed position with respect tothe first mirror positioned so that the camera can view reflected imagesof the object orientation marker in the second mirror simultaneouslywith reflected images of the object orientation marker in the firstmirror; a mirror orientation marker in a fixed position with respect tothe first mirror positioned so that the camera can view direct images ofthe mirror orientation marker simultaneously with reflected images ofthe object orientation marker in both the first mirror and the secondmirror; a motion tracking computer that analyzes repeated reflectedimages of the object orientation marker in the first mirror, repeatedreflected images of the object orientation marker in the second mirrorand repeated direct images of the mirror orientation marker, todetermine motion of the object between the repeated images and to sendtracking information to the scanner to dynamically adjust scans tocompensate for motion of said object.
 7. A motion tracking system for anobject in the scanning volume of a scanner, comprising: a camera thatrecords repeated images; an object orientation marker attached to theobject; a first mirror in a fixed position with respect to the scannerpositioned so that the camera can view the object orientation marker inthe first mirror; a mirror orientation marker in a fixed position withrespect to the first mirror positioned so that the camera can view adirect image of the mirror orientation marker simultaneously with areflected image in the first mirror of the object orientation marker; amotion tracking computer that analyzes repeated reflected images of theobject orientation marker in the first mirror and repeated direct imagesof the mirror orientation marker to determine motion of the objectbetween the repeated images and to send tracking information to thescanner to dynamically adjust scans to compensate for motion of saidobject.
 8. A system according to any one of claims 5, 6 or 7, whereinthe mirrors and camera can be internally calibrated by analyzing therepeated images.
 9. A system according to claim 8, whereby patientmotion is recorded both by scans of the object by the scanner and byrepeated images of the object orientation marker, so that such patientmotion is recorded in coordinate frames of both the scanner and of thecamera and mirrors, whereby patient motion recorded in the coordinateframe of the camera and mirrors can be transformed into patient motionin the coordinate frame of the scanner.
 10. A process for using anobject orientation marker, comprising: attaching said object orientationmarker to an object being scanned in a scanner; detecting motion of saidobject orientation marker while said object is being scanned to generatetracking information; and sending said tracking information to saidscanner to dynamically adjust said scanner to compensate for said motionof said object.
 11. A system according to any one of claims 1, 2 or 5,further comprising prediction means to predict orientation of the objectat times when scans will be taken by the scanner.
 12. A system accordingto claim 11, wherein said scanner is selected from the group consistingof MR scanners, PET scanners, SPECT scanners, CT scanners, and digitalangiographic scanners.
 13. A system according to claim 11, wherein saidobject orientation marker indicates pose in at least 3 degrees offreedom.
 14. A system according to claim 11, wherein said objectorientation marker indicates pose in 6 degrees of freedom.
 15. A systemaccording to claim 11, wherein said object orientation marker is an RGR.16. A system comprising: an adaptive imaging system; a motion trackingsystem; and a motion filtering and prediction system; wherein the motiontracking system provides tracking information to the adaptive imagingsystem to dynamically adjust scans to compensate for motion of saidobject; and wherein the motion filtering and prediction system providespredicted pose of the object when the imaging system takes scans.